# Libraries
library(tidyverse)
library(sf)
library(USAboundaries)
library(sp)
library(leaflet)
library(plotly)
library(lubridate)
library(RColorBrewer)

Measurement threshold (1920 - 2019)

A minimum threshold of 10 distinct measurements with at least 1 measurement every 5 years was applied to filter for only the regularly monitored wells. investigate regularly monitored wells

Active Management Areas

The 1980 Arizona Groundwater code established 8 Active management areas (AMA) in areas heavily reliant on mined groundwater. The goal of the AMAs is too achieve safe yield groundwater usage in these heavy groundwater pumping areas.

Joseph City AMA

Prescott AMA

Pheonix AMA

Harquahala AMA

Pinal AMA

Tucson AMA

Douglas AMA

Santa Cruz AMA

Buffer analysis on deep water wells

Investigation of wells below 300ft in which depth has continually decreased. The first plot shows all wells within a certain depth range that have had continuous measurement records for over 50 years. The following plots focus on a specific well in that range, and then a buffer was formed around these wells (12 - 20 km) to then see what is happening to other wells within the same area. The buffer analysis was used on individual wells that displayed dramatic and continual decreases in depth to water.

Range: 300 - 500 ft

Well 4573

Well 4740

Well 3472

Range: 400 - 500 ft

Well 4401

Well 4182

Range: 500 - 600 ft

Well 4993

Well 5730

Well 4953

Well 1853

Well 5743

Negative DTW measurements

A negative DTW reading may indicate groundwater emerging above the surface in the form of a spring. There are 9 wells that recorded negative depth to water readings. In the area of Chino Valley there are 6 wells with negative DTW to water readings all within a 5 km radius of one another. They other 3 wells are located in the far southeast corner of Arizona, nearing the US-Mexico border.

Chino Valley

Southeast Arizona

Well 222

Well 524

Functions

### PLOT AN INDIVIDUAL WELL BY WELL ID (DTW TIME SERIES)

### PLOT AN INDIVIDUAL WELL BY WELL ID (DTW TIME SERIES)
plotWell = function(df_time, num) {
  font = list(
    family = 'Courier',
    size = 15,
    color = 'white')
  label = list(
    bgcolor = '#232F34',
    bordercolor = 'transparent',
    font = font)
  well = df_time %>% filter(wellid == num)
  gg = ggplot(data = well, aes(x = date, y = dtw)) +
    geom_line(data = well, aes(y = dtw, col = wellid), size = 1) +
    ylim(max(well$dtw) + 100, 0) +
    labs(x = 'Year',
         y = 'DTW (ft)',
         col = 'Well') +  
    theme_bw() +
    theme(plot.title = element_text(face = 'bold',color = 'black', size = 18, hjust = 0.5), 
          axis.text.x = element_text(color="black", size=14), 
          axis.text.y = element_text(color="black", size=14), 
          axis.title.x = element_text(face="bold", color="black", size=16), 
          axis.title.y = element_text(face="bold", color="black", size=16), 
          panel.grid.major = element_line(colour = "#808080"),
          panel.grid.minor = element_line(colour = "#808080", size = 1))
  plot = ggplotly(gg, tooltip = c('x', 'y', 'wellid')) %>%
    style(hoverlabel = label) %>% 
    layout(font = font, 
           yaxis = list(fixedrange = TRUE)) %>% 
    config(displayModeBar = FALSE)
  plot
}

# PLOTS WELL DTW TIME SERIES WITHIN A RANGE (MIN, MAX)
plotRange = function(df_time, min, max) {
  font = list(
    family = 'Courier',
    size = 15,
    color = 'white')
  label = list(
    bgcolor = '#232F34',
    bordercolor = 'transparent',
    font = font)
  df_time = df_time %>% filter(dtw <= max, dtw >= min) %>% 
    arrange(desc(date))
  gg = ggplot(data = df_time, aes(x = date, y = dtw)) +
    geom_line(aes(y = dtw, col = wellid), size = 1) +
    ylim(max(df_time$dtw) + 50, min(df_time$dtw)) +
    labs(x = 'Year',
         y = 'DTW (ft)') + 
    theme_bw() +
    theme(plot.title = element_text(face = 'bold',color = 'black', size = 18, hjust = 0.5), 
          axis.text.x = element_text(color="black", size=14), 
          axis.text.y = element_text(color="black", size=14), 
          axis.title.x = element_text(face="bold", color="black", size=16), 
          axis.title.y = element_text(face="bold", color="black", size=16), 
          panel.grid.major = element_line(colour = "#808080"),
          panel.grid.minor = element_line(colour = "#808080", size = 1))
  plot = ggplotly(gg, tooltip = c('x', 'y', 'wellid')) %>%
    style(hoverlabel = label) %>% 
    layout(font = font, 
           yaxis = list(fixedrange = TRUE)) %>% 
    config(displayModeBar = FALSE)
  plot
  
}

# PLOTS WELL DTW TIME SERIES FROM DATAFRAME
plotMultipleWells = function(df_time) {
  font = list(
    family = 'Courier',
    size = 15,
    color = 'white')
   label = list(
    bgcolor = '#232F34',
    bordercolor = 'transparent',
    font = font)

  gg = ggplot(data = df_time, aes(x = date, y = dtw)) +
    geom_line(aes(y = dtw, col = wellid), size = 1) +
    ylim(max(df_time$dtw) + 50, 0) +
    labs(x = 'Year',
         y = 'DTW (ft)',
         col = 'Well') +  
    theme_bw() +
    theme(plot.title = element_text(face = 'bold',color = 'black', size = 18, hjust = 0.5), 
          axis.text.x = element_text(color="black", size=14), 
          axis.text.y = element_text(color="black", size=14), 
          axis.title.x = element_text(face="bold", color="black", size=16), 
          axis.title.y = element_text(face="bold", color="black", size=16), 
          panel.grid.major = element_line(colour = "#808080"),
          panel.grid.minor = element_line(colour = "#808080", size = 1))
  plot = ggplotly(gg, tooltip = c('x', 'y', 'wellid')) %>%
    style(hoverlabel = label) %>% 
    layout(font = font, 
           yaxis = list(fixedrange = TRUE)) %>% 
    config(displayModeBar = FALSE)
  plot
}

# IDENTICAL FUNCTION TO plotMultipleWells() BUT WILL PLOT ABOVE ZERO ON THE Y-AXIS
plotNegativeWells = function(df_time) {
  font = list(
    family = 'Courier',
    size = 15,
    color = 'white')
  label = list(
    bgcolor = '#232F34',
    bordercolor = 'transparent',
    font = font)
  gg = ggplot(data = df_time, aes(x = date, y = dtw)) +
    geom_line(aes(y = dtw, col = as.character(wellid)), size = 1) +
    geom_hline(aes(yintercept = 0), size = 1) +
    scale_y_reverse() +
    labs(x = 'Year',
         y = 'DTW (ft)',
         col = 'Well') + 
    theme_bw() +
    theme(plot.title = element_text(face = 'bold',color = 'black', size = 18, hjust = 0.5), 
          axis.text.x = element_text(color="black", size=14), 
          axis.text.y = element_text(color="black", size=14), 
          axis.title.x = element_text(face="bold", color="black", size=16), 
          axis.title.y = element_text(face="bold", color="black", size=16), 
          panel.grid.major = element_line(colour = "#808080"),
          panel.grid.minor = element_line(colour = "#808080", size = 1),
          legend.title = element_text(colour="black", size=16, face="bold"),
          legend.text = element_text(colour="black", size=10, face="bold"))
  plot = ggplotly(gg, tooltip = c('x', 'y', 'wellid')) %>%
    style(hoverlabel = label) %>% 
    layout(font = font, 
           yaxis = list(fixedrange = TRUE)) %>% 
    config(displayModeBar = FALSE)
  plot
}

# RETURNS A TIME SERIES PLOT OF WELLS WITHIN A BUFFER DISTANCE (km)
plotBuffer = function(df, id, buffer) {
  font = list(
    family = 'Courier',
    size = 15,
    color = 'white')
  label = list(
    bgcolor = '#232F34',
    bordercolor = 'transparent',
    font = font)
  well = df %>% filter(wellid == !!id)
  buff = st_buffer(df[well, ], buffer)
  nearby =st_intersection(df, buff)         
  df_time = join_time %>% filter(time_span > 50, wellid %in% nearby$wellid) 
  
  gg = ggplot(data = df_time, aes(x = date, y = dtw)) +
    geom_line(aes(y = dtw, col = wellid), size = 1) +
    ylim(1000, 0) +
    labs(x = 'Year',
         y = 'DTW (ft)',
         col = 'Well') +
    theme_bw() +
    theme(plot.title = element_text(face = 'bold',color = 'black', size = 18, hjust = 0.5),
          axis.text.x = element_text(color="black", size=14),
          axis.text.y = element_text(color="black", size=14),
          axis.title.x = element_text(face="bold", color="black", size=16),
          axis.title.y = element_text(face="bold", color="black", size=16),
          panel.grid.major = element_line(colour = "#808080"),
          panel.grid.minor = element_line(colour = "#808080", size = 1))
  plot = ggplotly(gg, tooltip = c('x', 'y', 'wellid')) %>%
    style(hoverlabel = label) %>% 
    layout(font = font, 
           yaxis = list(fixedrange = TRUE)) %>% 
    config(displayModeBar = FALSE)
  plot
}


# PLOTS A BUFFER AROUND SPECIFIED WELL AND LOCATES OTHER WELLS INSIDE THE BUFFER AREA
buffer_fun = function(df, well, buff, state) {
  buffer = st_buffer(df[well,], buff)
  near1 = st_intersection(df[,], buffer) %>% filter(measurement_dist >= 10)
  
  plot = ggplot() + 
    geom_sf(data = state) +
    geom_sf(data = buffer, fill = NA) + 
    geom_sf(data = near1, col = "red", size = .5) + 
    labs(caption = paste(nrow(near1), 'wells')) +
    theme_void() +
    theme(plot.caption = element_text(size = 22, face = "bold", hjust = 0.5))
  print(plot)
  return(near1)
}

# RETURNS DATAFRAME OF WELLS IN DTW RANGE (MIN - MAX)
dtw_range = function(df, min, max) {
  df = df %>% filter(dtw <= max, dtw >= min) %>% 
    mutate(sd = sd(dtw)) %>% 
    arrange(desc(date))
  return(df)
}

Arizona Groundwater research

Angus Watters -